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- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2017 International Conference on Optical Network Design and Modeling (ONDM) - Budapest (2017.5.15-2017.5.18)] 2017 International Conference on Optical Network Design and Modeling (ONDM) - Orchestrating data-intensive vNF service chains in inter-DC elastic optical networks
摘要： We investigate the problem of data-intensive vNF service chain (vNF-SC) orchestration in inter-datacenter EONs. After analyzing the N P-hardness of this problem, we solve it in a sequential manner by optimizing both the request serving sequence and the data-intensive vNF-SC orchestration. Specifically, we propose a request sorting algorithm and a data-intensive vNF-SC orchestration algorithm based on dynamic programming to minimize the service completion time. We conduct simulations to evaluate the proposed algorithms, and simulation results verify their effectiveness.
关键词： Network Function Virtualization,vNF Service Chain,Bulk-Data Transfer,Elastic optical networks
更新于2025-09-23 15:22:29
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[IEEE OCEANS 2019 - Marseille - Marseille, France (2019.6.17-2019.6.20)] OCEANS 2019 - Marseille - Experiments of Recreating the Frequency Domain Properties of Seawater Channel for Underwater Optical Communication
摘要： Mobile Edge Computing (MEC) has recently emerged as a promising technology to push the cloud frontier to the network edge, provisioning network services in close proximity of mobile users. Serving users at edge clouds has many advantages, such as reducing service delay, lower operational cost, and improved network resource availability. Furthermore, providing virtualized network service in MEC can improve user service experience, simplify network service deployments, and ease network resource management. However, provisioning reliable and seamless virtualized network services for mobile users while meeting their individual stringent delay requirements is of signi?cant importance and challenging. In this paper, we study mobile users requesting for virtualized network function services in MEC. We ?rst formulate two novel user request admission problems that take into account user mobility and service delay requirements. One is to minimize the admission cost of all user requests, assuming that there are suf?cient resources in MEC to meet user resource demands; the other is to maximize the accumulative network utility, subject to resource capacities of cloudlets, where the utility gain by admitting a request is determined by its resource demand and delay requirement, and the requested resource utilization in MEC. We then devise ef?cient approximation algorithms for the two problems. We ?nally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrate that the proposed algorithms are promising.
关键词： Network Function Virtualization,MEC,delay-sensitive,NFV,user mobility,Mobile Edge Computing,VNF service replication
更新于2025-09-11 14:15:04
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[IEEE 2018 20th International Conference on Transparent Optical Networks (ICTON) - Bucharest (2018.7.1-2018.7.5)] 2018 20th International Conference on Transparent Optical Networks (ICTON) - Accelerating VNF-based Deep Packet Inspection with the use of GPUs
摘要： Network Function Virtualization (NFV) replaces the hardware that supports packet processing in network operation from specific- by general-purpose ones, reducing costs and bringing more flexibility and agility to the network operation. However, this shift can cause performance losses due to the non-optimal packet processing capabilities of the general-purpose hardware. Moreover, supporting the line rate of optical network channels with Virtualized Network Functions (VNFs) is a challenging task. This work analyzes the benefits of using Graphics Processing Units (GPUs) to support the execution of a Deep Packet Inspection (DPI) VNF towards supporting the line rate of an optical channel. The use of GPUs in VNFs has a great potential to increase throughput, but the delay incurred might be an issue for some functions. Our simulation was performed using an Intrusion Detection Systems (IDS) which performs DPI deployed as a VNF under real-world traffic scaled to high bit rates. Results show that the packet processing speedup achieved by using GPUs can reach up to 19 times, at the expense of a higher packet delay.
关键词： Intrusion Detection System,Deep Packet Inspection,Graphics Processing Unit,Network Function Virtualization
更新于2025-09-10 09:29:36
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[IEEE 2018 20th International Conference on Transparent Optical Networks (ICTON) - Bucharest (2018.7.1-2018.7.5)] 2018 20th International Conference on Transparent Optical Networks (ICTON) - Processing and Bandwidth Resource Allocation in Multi-Provider NFV Cloud Infrastructures interconnected by Elastic Optical Networks
摘要： The paper proposes and investigates solutions to the computing and bandwidth resource allocation problem in Multi-Provider Network Function Virtualization (NFV) environment. The scenario is characterized by Cloud Infrastructures (CI) managed by different providers and interconnected by an Elastic Optical Networks (EON). The objective is to allocate resources for a given number of Service Function Chains (SFC) known in advance so as to minimize the sum of the processing and bandwidth costs and to take into account both the different processing costs charged by the Cloud Infrastructure (CI) providers and the sub-carrier consecutiveness, spectrum continuity and spectrum clash constraints. In particular we evaluate the operational cost saving that the proposed solutions allow us to obtain with respect to the case in which traditional resource allocation algorithms are applied.
关键词： Computing Resources,Bandwidth Resources,Elastic Optical Networks,Network Function Virtualization
更新于2025-09-10 09:29:36
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Deep-Learning-Assisted Network Orchestration for On-Demand and Cost-Effective vNF Service Chaining in Inter-DC Elastic Optical Networks
摘要： This work addresses the relatively long setup latency and complicated network control and management caused by on-demand virtual network function service chain (vNF-SC) provisioning in inter-datacenter elastic optical networks. We first design a provisioning framework with resource pre-deployment to resolve the aforementioned challenge. Specifically, the framework is designed as a discrete-time system, in which the operations are performed periodically in fixed time slots (TS). Each TS includes a pre-deployment phase followed by a provisioning phase. In the pre-deployment phase, a deep-learning (DL) model is designed to predict future vNF-SC requests, then lightpath establishment and vNF deployment are performed accordingly to pre-deploy resources for the predicted requests. Then, the system proceeds to the provisioning phase, which collects dynamic vNF-SC requests from clients and serves them in real-time by steering their traffic through the required vNFs in sequence. In order to forecast the high-dimensional data of future vNF-SC requests accurately, we design our DL model based on the long/short-term memory-based neural network and develop an effective training scheme for it. Then, the provisioning framework and DL model are optimized from several perspectives. We evaluate our proposed framework with simulations that leverage real traffic traces. The results indicate that our DL model achieves higher request prediction accuracy and lower blocking probability than two benchmarks that also predict vNF-SC requests and follow the principle of the proposed provisioning framework.
关键词： Long/short-term memory (LSTM),Elastic optical networks (EONs),Datacenter (DC),Service chaining,Network function virtualization (NFV),Deep learning
更新于2025-09-09 09:28:46